In 16 “undisclosed locations” across northern Los Angeles, digital eyes watch the public. These aren’t ordinary police-surveillance cameras; these cameras are looking at your face. Using facial-recognition software, the cameras can recognize individuals from up to 600 feet away. The faces they collect are then compared, in real-time, against “hot lists” of people suspected of gang activity or having an open arrest warrant.

Considering arrest and incarceration rates across L.A., chances are high that those hot lists disproportionately implicate African Americans. And recent research suggests that the algorithms behind facial-recognition technology may perform worse on precisely this demographic. Facial-recognition systems are more likely either to misidentify or fail to identify African Americans than other races, errors that could result in innocent citizens being marked as suspects in crimes. And though this technology is being rolled out by law enforcement across the country, little is being done to explore—or correct—for the bias.

State and local police began using facial recognition in the early 2000s. The early systems were notoriously unreliable, but today law-enforcement agencies in Chicago, Dallas, West Virginia, and elsewhere have acquired or are actively considering more sophisticated surveillance camera systems. Some of these systems can capture the faces of passersby and identify them in real-time. Sheriff’s departments across Florida and Southern California have been outfitted with smartphone or tablet facial recognition systems that can be used to run drivers and pedestrians against mug shot databases. In fact, Florida and several other states enroll every driver’s license photo in their facial recognition databases. Now, with the click of a button, many police departments can identify a suspect caught committing a crime on camera, verify the identity of a driver who does not produce a license, or search a state driver’s license database for suspected fugitives.

The limited testing that has been done on these systems has uncovered a pattern of racial bias.

But as with any emerging technology, facial recognition is far from perfect. Companies market facial recognition technology as “a highly efficient and accurate tool” with “an identification rate above 95 percent.” In reality, these claims are almost impossible to verify. The facial-recognition algorithms used by police are not required to undergo public or independent testing to determine accuracy or check for bias before being deployed on everyday citizens. More worrying still, the limited testing that has been done on these systems has uncovered a pattern of racial bias.

The National Institute of Standards and Technologies (NIST) conducts voluntary tests of facial-recognition vendors every four years. In 2010, NIST observed that accuracy rates had improved tenfold between each round of testing, a dramatic testament to the technology’s rapid advances.

But research suggests that the improving accuracy rates are not distributed equally. To the contrary, many algorithms display troubling differences in accuracy across race, gender, and other demographics. A 2011 study, co-authored by one of the organizers of NIST’s vendor tests, found that algorithms developed in China, Japan, and South Korea recognized East Asian faces far more readily than Caucasians. The reverse was true for algorithms developed in France, Germany, and the United States, which were significantly better at recognizing Caucasian facial characteristics. This suggests that the conditions in which an algorithm is created—particularly the racial makeup of its development team and test photo databases—can influence the accuracy of its results.

Similarly, a study conducted in 2012 that used a collection of mug shots from Pinellas County, Florida to test the algorithms of three commercial vendors also uncovered evidence of racial bias. Among the companies evaluated was Cognitec, whose algorithms are used by police in California, Maryland, Pennsylvania, and elsewhere. The study, co-authored by a senior FBI technologist, found that all three algorithms consistently performed 5-to-10 percent worse on African Americans than on Caucasians. One algorithm, which failed to identify the right person in 1 out of 10 encounters with Caucasian subjects, failed nearly twice as often when the photo was of an African American.

The closest match is treated as a lead, and police begin investigating an innocent person.

This bias is particularly unsettling in the context of the vast racial disparities that already exist in police traffic stop, stop and frisk, and arrest rates across the country. African Americans are at least twice as likely to be arrested as members of any other race in the United States and, by some estimates, up to 2.5 times more likely to be targeted by police surveillance. This overrepresentation in both mug shot databases and surveillance photos will compound the impact of that 5-to-10 percent difference in accuracy rates. In other words, not only are African Americans more likely to be misidentified by a facial-recognition system, they’re also more likely to be enrolled in those systems and be subject to their processing.

Imagine police are investigating a robbery that was caught on camera. When they run a video still of the suspect’s face against their facial-recognition database, they receive 10 possible matches, but none are a perfect match to the suspect. Nonetheless, the closest match is treated as a lead, and police begin investigating an innocent person. Thanks to the accuracy-rate bias in facial-recognition algorithms today, this scenario is statistically more likely to happen to an African American than a white person.

This is not to say that facial-recognition algorithms are “racist,” or that racial bias has been intentionally introduced into how they operate. Rather these demonstrated disparities may be introduced unintentionally at a number of points in the process of designing and deploying a facial recognition system. The engineer that develops an algorithm may program it to focus on facial features that are more easily distinguishable in some races than in others—the shape of a person’s eyes, the width of the nose, the size of the mouth or chin. This decision, in turn, might be based on preexisting biological research about face identification and past practices which themselves may contain bias. Or the engineer may rely on his or her own experience in distinguishing between faces—a process that is influenced by the engineer’s own race.

An algorithm trained exclusively on either African American or Caucasian faces recognized members of the race in its training set more readily than members of any other race.

In addition, algorithms learn how to calculate the similarity of photos by practicing on pre-existing training sets of faces. So even if the features on which an algorithm focuses are race-neutral, a training set of images that contains disproportionate numbers of one race will bias the algorithm’s accuracy rates in that direction. The 2012 study on mug shots found that an algorithm trained exclusively on either African American or Caucasian faces recognized members of the race in its training set more readily than members of any other race.

Unfortunately, the two studies discussed here are among the only works on racial bias published in the past decade—far too little review for a technology with the power to implicate people as suspects in a criminal investigation. NIST is well placed to lead the development of a comprehensive set of bias tests that could, alongside its existing regime, form the basis of a formal certification framework for facial recognition systems. But NIST testing of facial recognition systems is voluntary. Law-enforcement agencies—or the city councils and state legislatures that pay their bills—are well-placed to require that facial recognition software vendors submit to NIST’s existing accuracy tests, and any new tests that it develops.

Until those requirements are put in place, facial-recognition vendors should voluntarily submit their algorithms to NIST’s existing testing regime and other public, peer-reviewed research to measure—and begin to correct—the racial bias in their algorithms.

In the meantime, we’re conducting an in-depth study on facial-recognition use by state and local law-enforcement agencies across the country. Our research, based on responses to Freedom of Information requests sent to more than 100 departments, aims to develop a clear picture of what these systems look like, how and on whom they are used, and what policies and legal standards—if any—are in place to constrain their use. The final report, to be released this summer, will include recommendations for government at the federal, state, and local level, the law enforcement agencies themselves, companies, and advocates on how to ensure this technology used in a manner consistent with privacy and civil liberty interests of all citizens, regardless of race.

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In the landscape where Mad Max: Fury Road was filmed, a scientist is trying to understand a natural phenomenon that has eluded explanation for decades.

One evening earlier this spring, German naturalist Norbert Jürgens strayed from his expedition in the Namib Desert. He walked away from his campsite beside Leopard Rock, a huge pile of schist slabs stacked like left-over roofing tiles, and into a vast plain ringed with red-burnished hills. He had 20 minutes of light left before sunset, and he intended to use them.

This next part may sound like a reenactment from a nature documentary, but trust me: This is how it went down.

Off by himself, Jürgens dropped down to his knees. He sank his well-tanned arms in the sand up to the elbows. As he rooted around, he told me later, he had a revelation.

At the time, I was watching from the top of Leopard Rock, which offered a bird’s-eye view of both Jürgens and his expedition’s quarry. Across the plain, seemingly stamped into its dry, stubbly grass, were circles of bare ground, each about the size of an aboveground pool. Jürgens, a professor at the University of Hamburg, was digging—and pondering—in one of these bare patches.

The class divide is already toxic, and is fast becoming unbridgeable. You’re probably part of the problem.

1. The Aristocracy Is Dead …

For about a week every year in my childhood, I was a member of one of America’s fading aristocracies. Sometimes around Christmas, more often on the Fourth of July, my family would take up residence at one of my grandparents’ country clubs in Chicago, Palm Beach, or Asheville, North Carolina. The breakfast buffets were magnificent, and Grandfather was a jovial host, always ready with a familiar story, rarely missing an opportunity for gentle instruction on proper club etiquette. At the age of 11 or 12, I gathered from him, between his puffs of cigar smoke, that we owed our weeks of plenty to Great-Grandfather, Colonel Robert W. Stewart, a Rough Rider with Teddy Roosevelt who made his fortune as the chairman of Standard Oil of Indiana in the 1920s. I was also given to understand that, for reasons traceable to some ancient and incomprehensible dispute, the Rockefellers were the mortal enemies of our clan.

The text reflected not only the president’s signature syntax, but also the clash between his desire for credit and his intuition to walk away.

Donald Trump’s approach to North Korea has always been an intensely personal one—the president contended that his sheer force of will and negotiating prowess would win the day, and rather than use intermediaries, he planned for a face-to-face meeting, with himself and Kim Jong Un on either side of a table.

So Trump’s notice on Thursday that he was canceling the June 12 summit in Singapore was fitting. It arrived in the form of a letter that appears to have been written by the president himself. The missive features a Trumpian mix of non sequiturs, braggadocio, insults, flattery, and half-truths. Whether the dramatic letter marks the end of the current process or is simply a negotiating feint, it matches the soap-operatic series of events that proceeded it. Either way, it displays the ongoing conflict between Trump’s desire for pageantry and credit and his longstanding dictum that one must be willing to walk away from the negotiating table.

The 9-year-old has built a huge following with profane Instagram posts, but the bravado of “the youngest flexer of the century” masks a sadder tale about fame and exploitation.

In mid-February, a mysterious 9-year-old by the name of Lil Tay began blowing up on Instagram.

“This is a message to all y’all broke-ass haters, y’all ain't doing it like Lil Tay,” she shouts as she hops into a red Mercedes, hands full of wads of cash. “This is why all y’all fucking haters hate me, bitch. This shit cost me $200,000. I’m only 9 years old. I don’t got no license, but I still drive this sports car, bitch. Your favorite rapper ain’t even doing it like Lil Tay.”

Referring to herself as “the youngest flexer of the century,” Lil Tay quickly garnered a fan base of millions, including big name YouTubers who saw an opportunity to capitalize on her wild persona. In late January, RiceGum, an extremely influential YouTube personality dedicated an entire roast video to Lil Tay.

A short—and by no means exhaustive—list of the open questions swirling around the president, his campaign, his company, and his family.

President Trump speculated on Tuesday that “if” the FBI placed a spy inside his campaign, that would be one of the greatest scandals in U.S. history. On Wednesday morning on Twitter, the “if” dropped away—and Trump asserted yesterday’s wild surmise as today’s fact. By afternoon, a vast claque of pro-Trump talkers repeated the president’s fantasies and falsehoods in their continuing project to represent Donald Trump as an innocent victim of a malicious conspiracy by the CIA, FBI, and Department of Justice.

The president’s claims are false, but they are not fantasies. They are strategies to fortify the minds of the president’s supporters against the ever-mounting evidence against the president. As Laurence Tribe and Joshua Matz show in their new book about impeachment, an agitated and committed minority can suffice to protect a president from facing justice for even the most strongly proven criminality.

As recently as the 1950s, possessing only middling intelligence was not likely to severely limit your life’s trajectory. IQ wasn’t a big factor in whom you married, where you lived, or what others thought of you. The qualifications for a good job, whether on an assembly line or behind a desk, mostly revolved around integrity, work ethic, and a knack for getting along—bosses didn’t routinely expect college degrees, much less ask to see SAT scores. As one account of the era put it, hiring decisions were “based on a candidate having a critical skill or two and on soft factors such as eagerness, appearance, family background, and physical characteristics.”

The 2010s, in contrast, are a terrible time to not be brainy. Those who consider themselves bright openly mock others for being less so. Even in this age of rampant concern over microaggressions and victimization, we maintain open season on the nonsmart. People who’d swerve off a cliff rather than use a pejorative for race, religion, physical appearance, or disability are all too happy to drop the s‑bomb: Indeed, degrading others for being “stupid” has become nearly automatic in all forms of disagreement.

The Americans and the North Koreans were all set for a historic meeting. Then they started talking about Libya.

Of all the countries that might have acted as a spoiler for the summit in Singapore between Donald Trump and Kim Jong Un—China, Russia, Japan, the United States and North Korea themselves—the one that doomed it was unexpected. It isn’t even involved in North Korea diplomacy and is locateda long 6,000 miles away from the Korean Peninsula. It’s Libya.

Yet Libya ought to have been top of mind. It’s notoriously difficult to determine what motivates the strategic choices and polices of North Korea’s leaders, but among the factors that has been evident for some time is Kim Jong Un’s fear of ending up like Muammar al-Qaddafi. The Libyan strongman was pulled from a drainage pipe and shot to death by his own people following a U.S.-led military intervention during the Arab Spring in 2011. The North Korean government views its development of nuclear weapons—a pursuit Qaddafi abandoned in the early 2000s, when his nuclear program was far less advanced than North Korea’s, in exchange for the easing of sanctions and other promised benefits—as its most reliable shield against a hostile United States that could very easily inflict a similar fate on Kim. We know this because the North Korean government has repeatedly said as much. “The Saddam Hussein regime in Iraq and the Gaddafi regime in Libya could not escape the fate of destruction after being deprived of their foundations for nuclear development and giving up nuclear programs of their own accord,” the state-run Korean Central News Agency observed in 2016.

The bombastic legal adviser to Stormy Daniels is taking cues from the era of O.J. Simpson and Monica Lewinsky.

On cable news these days, there are very few people who have approached President Trump’s ubiquity. In fact, there is only one, and his name is Michael Avenatti. (Stormy who?)

Avenatti is not the first attorney to understand how the publicity game is played. Litigators are often like this: brash, aggressive, and sophisticated media manipulators. But Avenatti is the first celebrity lawyer of the Trump age, and it’s for that reason that he has become ultra-famous: Everything to do with Trump becomes, for good or ill, a star. And so it is with Avenatti, who in the public imagination has become not just “Stormy Daniels’s lawyer Michael Avenatti,” but simply “Michael Avenatti,” and appears to live inside your TV set.

The billionaire’s Twitter tirade was so ill-informed it led to a subtweet from his former head of communications.

Elon Musk’s screed against the media began with a story about Tesla.

“The holier-than-thou hypocrisy of big media companies who lay claim to the truth, but publish only enough to sugarcoat the lie, is why the public no longer respects them,” the entrepreneur tweeted Wednesday, with a link to a post on the website Electrek. The author of that post criticized news coverage of recent Tesla crashes and delays in the production of the Model 3, calling it “obsessive” and saying there’s been a “general increase of misleading clickbait.”

Musk followed that tweet with an hours-long tirade in which he suggested that journalists write negative stories about Tesla to get “max clicks” and “earn advertising dollars or get fired,” blamed the press for the election of President Donald Trump, and polled users on whether he should create a website that rates “the core truth” of articles and tracks “the credibility score” of journalists, which he would consider naming Pravda, like the Soviet state-run, propaganda-ridden news agency.

The president sent a terse note to North Korea’s leader, citing “the tremendous anger and open hostility displayed in your most recent statement.”

It was going to be the first meeting between an American president and a North Korean leader in history—an audacious effort to resolve the crisis over North Korea’s development of nuclear weapons. But on Thursday—after days of bitter back-and-forth between the United States and North Korea over how to approach denuclearization, with a North Korean official threatening a “nuclear-to-nuclear showdown” with the U.S. even as the North Korean government destroyed a nuclear test site as a show of good faith—the White House abruptly announced that the June 12 summit in Singapore would not take place.

The news came in a letter from Donald Trump to Kim Jong Un, the full text of which is here:

Dear Mr. Chairman:

We greatly appreciate your time, patience, and effort with respect to our recent negotiations and discussions relative to a summit long sought by both parties, which was scheduled to take place on June 12 in Singapore. We were informed that the meeting was requested by North Korea, but that to us is totally irrelevant. I was very much looking forward to being there with you. Sadly, based on the tremendous anger and open hostility displayed in your most recent statement, I feel it is inappropriate, at this time, to have this long-planned meeting. Therefore, please let this letter serve to represent that the Singapore summit, for the good of both parties, but to the detriment of the world, will not take place. You talk about your nuclear capabilities, but ours are so massive and powerful that I pray to God they will never have to be used.

I felt a wonderful dialogue was building up between you and me, and ultimately, it is only that dialogue that matters. Some day, I look very much forward to meeting you. In the meantime, I want to thank you for the release of the hostages who are now home with their families. That was a beautiful gesture and was very much appreciated.

If you change your mind having to do with this most important summit, please do not hesitate to call me or write. The world, and North Korea in particular, has lost a great opportunity for lasting peace and great prosperity and wealth. This missed opportunity is a truly sad moment in history.